Search results for: type-2 fuzzy sets

Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

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In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

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Authors: Lin Li, P. G. R. N. I. Pussella

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When representing spatial data and their attributes on different types of maps, the scale plays a key role in the process of map generalization. The process is consisted with two main operators such as selection and omission. Once some data were selected, they would undergo of several geometrical changing processes such as elimination, simplification, smoothing, exaggeration, displacement, aggregation and size reduction. As a result of these operations at different levels of data, the geometry of the spatial features such as length, sinuosity, orientation, perimeter and area would be altered. This would be worst in the case of preparation of small scale maps, since the cartographer has not enough space to represent all the features on the map. What the GIS users do is when they wanted to analyze a set of spatial data; they retrieve a data set and does the analysis part without considering very important characteristics such as the scale, the purpose of the map and the degree of generalization. Further, the GIS users use and compare different maps with different degrees of generalization. Sometimes, GIS users are going beyond the scale of the source map using zoom in facility and violate the basic cartographic rule 'it is not suitable to create a larger scale map using a smaller scale map'. In the study, the effect of map generalization for GIS analysis would be discussed as the main objective. It was used three digital maps with different scales such as 1:10000, 1:50000 and 1:250000 which were prepared by the Survey Department of Sri Lanka, the National Mapping Agency of Sri Lanka. It was used common features which were on above three maps and an overlay analysis was done by repeating the data with different combinations. Road data, River data and Land use data sets were used for the study. A simple model, to find the best place for a wild life park, was used to identify the effects. The results show remarkable effects on different degrees of generalization processes. It can see that different locations with different geometries were received as the outputs from this analysis. The study suggests that there should be reasonable methods to overcome this effect. It can be recommended that, as a solution, it would be very reasonable to take all the data sets into a common scale and do the analysis part.

Keywords: generalization, GIS, scales, spatial analysis

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Authors: Takashi Mitsuishi, Koji Saigusa

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This paper presents circular polar coordinates transformation of periodic fuzzy membership function. The purpose is identification of domain of periodic membership functions in consequent part of IF-THEN rules. The proposed methods are applied to the simple color construct system.

Keywords: periodic membership function, polar coordinates transformation, defuzzification, circular coordinates

Procedia PDF Downloads 305

Authors: Rajrupa Ghosh, Abhijit Mitra

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Future use of animal protein sources in prawn feeds is expected to be considerably reduced as a consequence of increasing economical, environmental and safety issues. Of main concern has been the use of expensive marine protein sources, such as fish meal which often results in fouling of water quality and disease outbreak in cultured species. To determine prawn capacity to use practical feeds with plant proteins as replacement ingredients to animal protein sources, 8-months growth trial was conducted in two sets of ponds using juvenile (0.02 gm) Macrobrachium rosenbergii. Among the two sets, one set (comprising of three ponds) is experimental pond included formulated feed prepared with 30% Porteresia coarctata dust along with other general ingredients and another set (comprising of another three ponds) is control pond with commercial feed. Mean final weight, percent weight gain, final net yield, feed conversion ratio and survival were evaluated. Higher condition index values, survival rate and gain in prawn weight were observed in experimental pond compared to control pond. Low FCR values were observed in the experimental pond than the control pond. Evaluation of production parameters at the end of the study demonstrated significant differences (P ≥ 0.05) among two ponds. The variation may be attributed to specially formulated plant based feed that not only boosted up the growth of prawns, but also upgraded the ambient aquatic health. These results indicate that fish meal can be replaced with algal protein sources in diets without affecting prawn growth and production.

Keywords: macrobrachium rosenbergii, porteresia coarctata, Indian sundarbans, feed

Procedia PDF Downloads 349

Authors: Taimaz Larimian, Negin Sadeghi

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Very little is known about the impacts of urban security on the level of social sustainability within the cities of developing countries. Urban security is still struggling to find its position in the social sustainability agenda, despite the significant role of safety and security on different aspects of peoples’ lives. This paper argues that urban safety and security should be better integrated within the social sustainability framework. With this aim, this study investigates the hypothesized relationship between social sustainability and Crime Prevention through Environmental Design (CPTED) approach at the neighborhood scale. This study proposes a model of key influential dimensions of CPTED analyzed into localized factors and sub-factors. These factors are then prioritized using pairwise comparison logic and fuzzy group Analytic Hierarchy Process (AHP) method in order to determine the relative importance of each factor on achieving social sustainability. The proposed model then investigates social sustainability in six case study neighborhoods of Isfahan city based on residents’ perceptions of safety within their neighborhood. Mixed method of data collection is used by using a self-administered questionnaire to explore the residents’ perceptions of social sustainability in their area of residency followed by an on-site observation to measure the CPTED construct. In all, 150 respondents from selected neighborhoods were involved in this research. The model indicates that CPTED approach has a significant direct influence on increasing social sustainability in neighborhood scale. According to the findings, among different dimensions of CPTED, ‘activity support’ and ‘image/ management’ have the most influence on people’s feeling of safety within studied areas. This model represents a useful designing tool in achieving urban safety and security during the development of more socially sustainable and user-friendly urban areas.

Keywords: crime prevention through environmental design (CPTED), developing countries, fuzzy analytic hierarchy process (FAHP), social sustainability

Procedia PDF Downloads 302

Authors: Mary Joy C. Montenegro, Voltaire M. Mistades

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This action research was implemented to enhance the teaching of linear motion and to improve students' conceptual understanding and engagement using a developed 7R-based module called 'module on vectors and one-dimensional kinematics' (MVOK). MVOK was validated in terms of objectives, contents, format, and language used, presentation, usefulness, and overall presentation. The validation process revealed a value of 4.7 interpreted as 'Very Acceptable' with a substantial agreement (0. 60) from the validators. One intact class of 46 Grade 12 STEM students from one of the public schools in Paranaque City served as the participants of this study. The students were taught using the module during the first semester of the academic year 2019–2020. Employing the mixed-method approach, quantitative data were gathered using pretest/posttest, activity sheets, problem sets, and survey form, while qualitative data were obtained from surveys, interviews, observations, and reflection log. After the implementation, there was a significant difference of 18.4 on students’ conceptual understanding as shown in their pre-test and post-test scores on the 24-item test with a moderate Hake gain equal to 0.45 and an effect size of 0.83. Moreover, the scores on activity and problem sets have a 'very good' to 'excellent' rating, which signifies an increase in the level of students’ conceptual understanding. There also exists a significant difference between the mean scores of students’ engagement overall (t= 4.79, p = 0.000, p < 0.05) and in the dimension of emotion (t = 2.51, p = 0.03) and participation/interaction (t = 5.75, p = 0.001). These findings were supported by gathered qualitative data. Positive views were elicited from the students since it is an accessible tool for learning and has well-detailed explanations and examples. The results of this study may substantiate that using MVOK will lead to better physics content understanding and higher engagement.

Keywords: conceptual understanding, engagement, linear motion, module

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Authors: I. Arockiarani

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The focus of the paper is to furnish the entropy measure for a neutrosophic set and neutrosophic soft set which is a measure of uncertainty and it permeates discourse and system. Various characterization of entropy measures are derived. Further we exemplify this concept by applying entropy in various real time decision making problems.

Keywords: entropy measure, Hausdorff distance, neutrosophic set, soft set

Procedia PDF Downloads 252

Authors: Mikhail Zimin, Svetlana Zimina, Maxim Zimin

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Without question, the basic method of prevention of human and material losses is the provision for adequate strength of constructions. At the same time, seismic load has a stochastic character. So, at all times, there is little danger of earthquake forces exceeding the selected design load. This risk is very low, but the consequences of such events may be extremely serious. Very dangerous are also occasional mistakes in seismic zoning, soil conditions changing before temblors, and failure to take into account hazardous natural phenomena caused by earthquakes. Besides, it is known that temblors detrimentally affect the environmental situation in regions where they occur, resulting in panic and worsening various disease courses. It may lead to mistakes of personnel of hazardous production facilities like the production and distribution of gas and oil, which may provoke severe accidents. In addition, gas and oil pipelines often have long mileage and cross many perilous zones by contrast with buildings. This situation increases the risk of heavy accidents. In such cases, complex monitoring of potential earthquake localities would be relevant. Even though the number of successful real-time forecasts of earthquakes is not great, it is well in excess, such as may be under random guessing. Experimental performed time-lapse study and analysis consist of searching seismic, biological, meteorological, and light earthquake precursors, processing such data with the help of fuzzy sets, collecting weather information, utilizing a database of terrain, and computing risk of slope processes under the temblor in a given setting. Works were done in a real-time environment and broadly acceptable results took place. Observations from already in-place seismic recording systems are used. Furthermore, a look back study of precursors of known earthquakes is done. Situations before Ashkhabad, Tashkent, and Haicheng seismic events are analyzed. Fairish findings are obtained. Results of earthquake forecasts can be used for predicting dangerous natural phenomena caused by temblors such as avalanches and mudslides. They may also be utilized for prophylaxis of some diseases and their complications. Relevant software is worked out too. It should be emphasized that such control does not require serious financial expenses and can be performed by a small group of professionals. Thus, complex monitoring of potential earthquake localities, including short-term earthquake forecasts and analysis of possible hazardous consequences of temblors, may further the safety of pipeline facilities.

Keywords: risk, earthquake, monitoring, forecast, precursor

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Authors: Sahin Emrah Amrahov, Fatih Aybar, Serhat Dogan

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In this paper we consider the rule reduct generation problem. Rule Reduct Generation (RG) and Modified Rule Generation (MRG) algorithms, that are used to solve this problem, are well-known. Alternative to these algorithms, we develop Pruning Rule Generation (PRG) algorithm. We compare the PRG algorithm with RG and MRG.

Keywords: rough sets, decision rules, rule induction, classification

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Authors: Choukri Lekbir, Mira Mokhtari

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Hydrogen-Materials interaction and mechanisms can be modeled at nano scale by quantum methods. In this work, the effect of hydrogen on the electronic properties of a cluster material model «nickel» has been studied by using of density functional theoretical (DFT) method. Two types of clusters are optimized: Nickel and hydrogen-nickel system. In the case of nickel clusters (n = 1-6) without presence of hydrogen, three types of electronic structures (neutral, cationic and anionic), have been optimized according to three basis sets calculations (B3LYP/LANL2DZ, PW91PW91/DGDZVP2, PBE/DGDZVP2). The comparison of binding energies and bond lengths of the three structures of nickel clusters (neutral, cationic and anionic) obtained by those basis sets, shows that the results of neutral and anionic nickel clusters are in good agreement with the experimental results. In the case of neutral and anionic nickel clusters, comparing energies and bond lengths obtained by the three bases, shows that the basis set PBE/DGDZVP2 is most suitable to experimental results. In the case of anionic nickel clusters (n = 1-6) with presence of hydrogen, the optimization of the hydrogen-nickel (anionic) structures by using of the basis set PBE/DGDZVP2, shows that the binding energies and bond lengths increase compared to those obtained in the case of anionic nickel clusters without the presence of hydrogen, that reveals the armor effect exerted by hydrogen on the electronic structure of nickel, which due to the storing of hydrogen energy within nickel clusters structures. The comparison between the bond lengths for both clusters shows the expansion effect of clusters geometry which due to hydrogen presence.

Keywords: binding energies, bond lengths, density functional theoretical, geometry optimization, hydrogen energy, nickel cluster

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Authors: Bushra Zafar, Usman Qamar

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Large data sample size and dimensions render the effectiveness of conventional data mining methodologies. A data mining technique are important tools for collection of knowledgeable information from variety of databases and provides supervised learning in the form of classification to design models to describe vital data classes while structure of the classifier is based on class attribute. Classification efficiency and accuracy are often influenced to great extent by noisy and undesirable features in real application data sets. The inherent natures of data set greatly masks its quality analysis and leave us with quite few practical approaches to use. To our knowledge first time, we present a new approach for investigation of structure and quality of datasets by providing a targeted analysis of localization of noisy and irrelevant features of data sets. Machine learning is based primarily on feature selection as pre-processing step which offers us to select few features from number of features as a subset by reducing the space according to certain evaluation criterion. The primary objective of this study is to trim down the scope of the given data sample by searching a small set of important features which may results into good classification performance. For this purpose, a heuristic for wrapper-based feature selection using genetic algorithm and for discriminative feature selection an external classifier are used. Selection of feature based on its number of occurrence in the chosen chromosomes. Sample dataset has been used to demonstrate proposed idea effectively. A proposed method has improved average accuracy of different datasets is about 95%. Experimental results illustrate that proposed algorithm increases the accuracy of prediction of different diseases.

Keywords: data mining, generic algorithm, KNN algorithms, wrapper based feature selection

Procedia PDF Downloads 314

Authors: Shraddha Srivastava, N. K. Painuly, S. P. Mishra, Navin Singh, Muhsin Punchankandy, Kirti Srivastava, M. L. B. Bhatt

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Various optimization methods used in interstitial brachytherapy are based on dwell positions and dwell weights alteration to produce dose distribution based on the implant geometry. Since these optimization schemes are not anatomy based, they could lead to deviations from the desired plan. This study was henceforth carried out to compare anatomy-based Inverse Planning Simulated Annealing (IPSA) optimization technique with graphical and geometrical optimization methods in interstitial high dose rate brachytherapy planning of cervical carcinoma. Six patients with 12 CT data sets of MUPIT implants in HDR brachytherapy of cervical cancer were prospectively studied. HR-CTV and organs at risk (OARs) were contoured in Oncentra treatment planning system (TPS) using GYN GEC-ESTRO guidelines on cervical carcinoma. Three sets of plans were generated for each fraction using IPSA, graphical optimization (GrOPT) and geometrical optimization (GOPT) methods. All patients were treated to a dose of 20 Gy in 2 fractions. The main objective was to cover at least 95% of HR-CTV with 100% of the prescribed dose (V100 ≥ 95% of HR-CTV). IPSA, GrOPT, and GOPT based plans were compared in terms of target coverage, OAR doses, homogeneity index (HI) and conformity index (COIN) using dose-volume histogram (DVH). Target volume coverage (mean V100) was found to be 93.980.87%, 91.341.02% and 85.052.84% for IPSA, GrOPT and GOPT plans respectively. Mean D90 (minimum dose received by 90% of HR-CTV) values for IPSA, GrOPT and GOPT plans were 10.19 ± 1.07 Gy, 10.17 ± 0.12 Gy and 7.99 ± 1.0 Gy respectively, while D100 (minimum dose received by 100% volume of HR-CTV) for IPSA, GrOPT and GOPT plans was 6.55 ± 0.85 Gy, 6.55 ± 0.65 Gy, 4.73 ± 0.14 Gy respectively. IPSA plans resulted in lower doses to the bladder (D₂

Keywords: cervical cancer, HDR brachytherapy, IPSA, MUPIT

Procedia PDF Downloads 180

Authors: D. Pugazhenthi, B. Sree Vidya

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Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

Procedia PDF Downloads 258

Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

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Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: dynamic modeling, missing data, mobility, multiple imputation

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Authors: Laurent Bellemare

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After the showcase of traditional Indonesian performing arts at the Vancouver Expo 1986, Canadian universities inherited sets of Indonesian gamelan orchestras and soon began offering courses for music students interested in learning these diverse traditions. Among them, Université de Montréal was offered two sets of Balinese orchestras, a novelty that allowed a community of Montreal gamelan enthusiasts to form and engage with this music. A few generations later, a large body of archives have amassed, framing the history of this niche community’s achievements. This data, scattered in public and private archive collections, comes in various formats: Digital Audio Tape, audio cassettes, Video Home System videotape, digital files, photos, reel-to-reel audiotape, posters, concert programs, letters, TV shows, reports and more. Attempting to study these documents in order to unearth a chronology of gamelan in Montreal has proven to be challenging since no suitable platform for preservation, storage, and research currently exists. These files are, therefore, hard to find due to their decentralized locations. Additionally, most of the documents in older formats have yet to be digitized. In the case of recent digital files, such as pictures or rehearsal recordings, their locations can be even messier and their quantity overwhelming. Aside from the basic issue of choosing a suitable repository platform, questions of legal rights and methodology arise. For posterity, these documents should nonetheless be digitized, organized, and stored in an easily accessible online repository. This paper aims to underline the various challenges encountered in the early stages of such a project as well as to suggest ways of overcoming the obstacles to a thorough archival investigation.

Keywords: archival work, archives, Balinese gamelan, Canada, Gamelan, Indonesia, Javanese gamelan, Montreal

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Authors: Ahdab H. Mahdaly, Debajyoti Pati, Sharran Parkinson, Lee S. Duemer

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The importance of providing employed mothers with the right physical environment inside the home is not an easy task, especially when the culture is involved. This study examines the typical Saudi home as a personal, emotional, social and cultural setting, especially on the interactions between the physical design and perceived control of working mothers. However, owing to the scarcity of published literature on Saudi homes, American employed mothers were included in the study to provide a baseline. With the ongoing transformations in women’s role in Saudi Arabia, there is a perception that traditional home designs may not afford the appropriate sense of control inside the home. Saudi Arabia has numerous interacting layers of socio-cultural-religious forces that affect residential design, and understanding the moderating role of the Saudi home is vital to the ongoing national policy transition on women. The study investigated one narrow, albeit critical, influence of home design on ones sense of control – direct visual and physical accessibility between sets of rooms. Ten subjects, five Saudis and five American, examined visual and physical access between 171 room sets, and provided qualitative responses on how each access influences their sense of control. Three main themes emerged, with potential effects on control: 1- Openness, 2- Proximity, and 3- Separation. Data suggest that although the Saudi home is a substantially more complex setting than the American ones, a class of spaces that can be termed as ‘Neutral Rooms’ serving as cultural separators may represent the ideal solution for optimizing sense of control, without ignoring cultural-religious traditions, during the transition of the Saudi women.

Keywords: direct physical accessibility, home environment, sense of control, visual accessibility, working mothers

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Authors: Abhishek N. Srivastava, Rahul Singh, Sumedha Chakma

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The rapid urbanization in the developing countries is generating an enormous amount of waste leading to the creation of unregulated landfill sites at various places at its disposal. The liquid waste, known as leachate, produced from these landfills sites is severely affecting the surrounding water quality. The water quality in the proximity areas of the landfill is found affected by various physico-chemical parameters of leachate such as pH, alkalinity, total hardness, conductivity, chloride, total dissolved solids (TDS), total suspended solids (TSS), sulphate, nitrate, phosphate, fluoride, sodium and potassium, biological parameters such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), Faecal coliform, and heavy metals such as cadmium (Cd), lead (Pb), iron (Fe), mercury (Hg), arsenic (As), cobalt (Co), manganese (Mn), zinc (Zn), copper (Cu), chromium (Cr), nickel (Ni). However, all these parameters are distributive in leachate that produced according to the nature of waste being dumped at various landfill sites, therefore, it becomes very difficult to predict the main responsible parameter of leachate for water quality contamination. The present study is endeavour the comparative analysis of the physical, chemical and biological parameters of various landfills in India viz. Okhla landfill, Ghazipur landfill, Bhalswa ladfill in NCR Delhi, Deonar landfill in Mumbai, Dhapa landfill in Kolkata and Kodungayaiyur landfill, Perungudi landfill in Chennai. The statistical analysis of the parameters was carried out using the Statistical Packages for the Social Sciences (SPSS) and LandSim 2.5 model to simulate the long term effect of various parameters on different time scale. Further, the uncertainties characterization of various input parameters has also been analysed using fuzzy alpha cut (FAC) technique to check the sensitivity of various water quality parameters at the proximity of numerous landfill sites. Finally, the study would help to suggest the best method for the prevention of pollution migration from the landfill sites on priority basis.

Keywords: landfill leachate, water quality, LandSim, fuzzy alpha cut

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Authors: Faisal A. Salih

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Vinpocetine (Vin) is an ethyl ester of apovincamic acid and is a semisynthetic derivative of vincamine, an alkaloid from plants of the genus Periwinkle (plant) vinca minor. It was found that this compound stimulates cerebral metabolism: it increases the uptake of glucose and oxygen, as well as the consumption of these substances by the brain tissue. Vinpocetine enhances the flow of blood in the brain and has a vasodilating, antihypertensive, and antiplatelet effect. Vinpocetine seems to improve the human ability to acquire new memories and restore memories that have been lost. This drug has been clinically used for the treatment of cerebrovascular disorders such as stroke and dementia memory disorders, as well as in ophthalmology and otorhinolaryngology. It has no side effects, and no toxicity has been reported when using vinpocetine for a long time. For the quantitative determination of Vin in dosage forms, the HPLC methods are generally used. A promising alternative is potentiometry with Vin- selective electrode, which does not require expensive equipment and materials. Another advantage of the potentiometric method is that the pills and solutions for injections can be used directly without separation from matrix components, which reduces both analysis time and cost. In this study, it was found that the choice of a good plasticizer an electrode with the following membrane composition: PVC (32.8 wt.%), ortho-nitrophenyl octyl ether (66.6 wt.%), tetrakis-4-chlorophenyl borate (0.6 wt.%) exhibits excellent analytical performance: lower detection limit (LDL) 1.2•10⁻⁷ M, linear response range (LRR) 1∙10⁻³–3.9∙10⁻⁶ M, the slope of the electrode function 56.2±0.2 mV/decade). Vin masses per average tablet weight determined by direct potentiometry (DP) and potentiometric titration (PT) methods for the two different sets of 10 tablets were (100.35±0.2–100.36±0.1) mg for two sets of blister packs. The mass fraction of Vin in individual tablets, determined using DP, was (9.87 ± 0.02–10.16 ±0.02) mg, while the RSD was (0.13–0.35%). The procedure has very good reproducibility, and excellent compliance with the declared amounts was observed.

Keywords: vinpocetine, potentiometry, ion selective electrode, pharmaceutical analysis

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Authors: Zhu-Qing Jia, Tao Lin, Tong Zhou

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The recognition method of Optical Character Recognition has been expensively utilized, while it is rare to be employed specifically in recognition of electronic components. This paper suggests a high-effective algorithm on appearance identification of integrated circuit components based on the existing methods of character recognition, and analyze the pros and cons.

Keywords: optical character recognition, fuzzy page identification, mutual correlation matrix, confidence self-adaptation

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Authors: Younis Jabarzadeh, Rahim Sarvari, Negar Ahmadi Alghalandis

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Entrepreneurship at both individual and organizational level is one of the most driving forces in economic development and leads to growth and competition, job generation and social development. Especially in developing countries, the role of entrepreneurship in economic and social prosperity is more emphasized. But the effect of global economic development on the environment is undeniable, especially in negative ways, and there is a need to rethink current business models and the way entrepreneurs act to introduce new businesses to address and embed environmental issues in order to achieve sustainable development. In this paper, green or sustainable entrepreneurship is addressed in Iran to identify challenges and barriers entrepreneurs in the economic and social sectors face in developing green business solutions. Sustainable or green entrepreneurship has been gaining interest among scholars in recent years and addressing its challenges and barriers need much more attention to fill the gap in the literature and facilitate the way those entrepreneurs are pursuing. This research comprised of two main phases: qualitative and quantitative. At qualitative phase, after a thorough literature review, fuzzy Delphi method is utilized to verify those challenges and barriers by gathering a panel of experts and surveying them. In this phase, several other contextually related factors were added to the list of identified barriers and challenges mentioned in the literature. Then, at the quantitative phase, Interpretive Structural Modeling is applied to construct a network of interactions among those barriers identified at the previous phase. Again, a panel of subject matter experts comprised of academic and industry experts was surveyed. The results of this study can be used by policymakers in both the public and industry sector, to introduce more systematic solutions to eliminate those barriers and help entrepreneurs overcome challenges of sustainable entrepreneurship. It also contributes to the literature as the first research in this type which deals with the barriers of sustainable entrepreneurship and explores their interaction.

Keywords: green entrepreneurship, barriers, fuzzy Delphi method, interpretive structural modeling

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Authors: Akhilesh Kumar, Sathyanarayan G., Nirmala S.

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An unusual approach is developed to determine the orbit of satellites/space objects. The determination of orbits is considered a boundary value problem and has been solved using the finite difference method (FDM). Only positions of the satellites/space objects are known at two end times taken as boundary conditions. The technique of finite difference has been used to calculate the orbit between end times. In this approach, the governing equation is defined as the satellite's equation of motion with a perturbed acceleration. Using the finite difference method, the governing equations and boundary conditions are discretized. The resulting system of algebraic equations is solved using Tri Diagonal Matrix Algorithm (TDMA) until convergence is achieved. This methodology test and evaluation has been done using all GPS satellite orbits from National Geospatial-Intelligence Agency (NGA) precise product for Doy 125, 2023. Towards this, two hours of twelve sets have been taken into consideration. Only positions at the end times of each twelve sets are considered boundary conditions. This algorithm is applied to all GPS satellites. Results achieved using FDM compared with the results of NGA precise orbits. The maximum RSS error for the position is 0.48 [m] and the velocity is 0.43 [mm/sec]. Also, the present algorithm is applied on the IRNSS satellites for Doy 220, 2023. The maximum RSS error for the position is 0.49 [m], and for velocity is 0.28 [mm/sec]. Next, a simulation has been done for a Highly Elliptical orbit for DOY 63, 2023, for the duration of 6 hours. The RSS of difference in position is 0.92 [m] and velocity is 1.58 [mm/sec] for the orbital speed of more than 5km/sec. Whereas the RSS of difference in position is 0.13 [m] and velocity is 0.12 [mm/sec] for the orbital speed less than 5km/sec. Results show that the newly created method is reliable and accurate. Further applications of the developed methodology include missile and spacecraft targeting, orbit design (mission planning), space rendezvous and interception, space debris correlation, and navigation solutions.

Keywords: finite difference method, grid generation, NavIC system, orbit perturbation

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: Shahriar Ghammamy, Masomeh Shahsavary

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In this paper, the optimized geometries and frequencies of the stationary point and the minimum energy paths of C13H12F7ClN2O are calculated by using the DFT (B3LYP) methods with LANL2DZ basis sets. B3LYP/ LANL2DZ calculation results indicated that some selected bond length and bond angles values for the C13H12F7ClN2O.

Keywords: C13H12F7ClN2O, vatural bond orbital, fluorous compounds, functional calculations

Procedia PDF Downloads 332

Authors: Mohammad Mahdi Hajiali

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Many of construction projects estimated in Iran have been influenced by the limitations of financial resources. As for Iran, a country that is developing, and to follow this development-oriented approach which many numbers of projects each year run in, if we can reduce the cost of projects by applying a method we will help greatly to minimize the cost of major construction projects and therefore projects will finish faster and more efficiently. One of the components of transportation infrastructure are roads that are considered to have a considerable share of the country budget. In addition, major budget of the related ministry is spending to repair, improve and maintain roads. Value Engineering is a simple and powerful methodology over the past six decades that has been successful in reducing the cost of many projects. Specific solution for using value engineering in the stage of project implementation is called value engineering change proposal (VECP). It was tried in this research to apply VECP in one of the road-building projects in Iran in order to enhance the value of this kind of projects and reduce their cost. In this case study after applying VECP, an idea was raised. It was about use of concrete pavement instead of hot mixed asphalt (HMA) and also using fiber in order to improve concrete pavement performance. VE group team made a decision that for choosing the best alternatives, get expert’s opinions in pavement systems and use Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) for ranking opinions of the experts. Finally, Jointed Plain Concrete Pavement (JPCP) was selected. Group also experimented concrete samples with available fibers in Iran and the results of experiments showed a significant increment in concrete specifications such as flexural strength. In the end, it was shown that by using of fiber-reinforced concrete pavement instead of asphalt pavement, we can achieve a significant saving in cost, time and also increment in quality, durability, and longevity.

Keywords: road-building projects, value engineering change proposal (VECP), Jointed Plain Concrete Pavement (JPCP), Fuzzy TOPSIS, fiber-reinforced concrete

Procedia PDF Downloads 192

Authors: Fils Olivier Kamanzi

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This research Paper shows that materials CFRP were used to rehabilitate 9 Beams and retrofitting of 9 Beams with size (125x250x2300) mm each for M50 grade of concrete with 20% of Volume of Cement replaced by GGBS as a mineral Admixture. Superplasticizer (ForscoConplast SP430) used to reduce the water-cement ratio and maintaining good workability of fresh concrete (Slump test 57mm). Concrete Mix ratio 1:1.56:2.66 with a water-cement ratio of 0.31(ACI codebooks). A sample of 6cubes sized (150X150X150) mm, 6cylinders sized (150ФX300H) mm and 6Prisms sized (100X100X500) mm were cast, cured, and tested for 7,14&28days by compressive, tensile and flexure test; finally, mix design reaches the compressive strength of 59.84N/mm2. 21 Beams were cast and cured for up to 28 days, 3Beams were tested by a two-point loading machine as Control beams. 9 Beams were distressed in flexure by adopting failure up to final Yielding point under two-point loading conditions by taking 90% off Ultimate load. Three sets, each composed of three distressed beams, were rehabilitated by using CFRP sheets, one, two & three layers, respectively, and after being retested up to failure mode. Another three sets were freshly retrofitted also by using CFRP sheets one, two & three layers, respectively, and being tested by a two-point load method of compression strength testing machine. The aim of this study is to determine the flexural Strength & behaviors of repaired and retrofitted Beams by CFRP sheets for gaining good strength and considering economic aspects. The results show that rehabilitated beams increase its strength 47 %, 78 % & 89 %, respectively, to thickness of CFRP sheets and 41%, 51 %& 68 %, respectively too, for retrofitted Beams. The conclusion is that three layers of CFRP sheets are the best applicable in repairing and retrofitting the bonded beams method.

Keywords: retrofitting, rehabilitation, cfrp, rcc beam, flexural strength and behaviors, ggbs, and epoxy resin

Procedia PDF Downloads 103

Authors: Zachary Pan

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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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Authors: Yasuyuki Takahashi, Hirotaka Shimada, Kyoko Saito

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Bone scintigraphy is widely used as a screening tool for bone metastases. However, the 180 to 240 minutes (min) waiting time after the intravenous (i.v.) injection of the tracer is both long and tiresome. To solve this shortcoming, a bone scan with a shorter waiting time is needed. In this study, we applied the Maximum Intensity Projection (MIP) and triple energy window (TEW) scatter correction to a whole body bone SPECT (Merged SPECT) and investigated shortening the waiting time. Methods: In a preliminary phantom study, hot gels of 99mTc-HMDP were inserted into sets of rods with diameters ranging from 4 to 19 mm. Each rod set covered a sector of a cylindrical phantom. The activity concentration of all rods was 2.5 times that of the background in the cylindrical body of the phantom. In the human study, SPECT images were obtained from chest to abdomen at 30 to 180 min after 99mTc- hydroxymethylene diphosphonate (HMDP) injection of healthy volunteers. For both studies, MIP images were reconstructed. Planar whole body images of the patients were also obtained. These were acquired at 200 min. The image quality of the SPECT and the planar images was compared. Additionally, 36 patients with breast cancer were scanned in the same way. The delectability of uptake regions (metastases) was compared visually. Results: In the phantom study, a 4 mm size hot gel was difficult to depict on the conventional SPECT, but MIP images could recognize it clearly. For both the healthy volunteers and the clinical patients, the accumulation of 99mTc-HMDP in the SPECT was good as early as 90 min. All findings of both image sets were in agreement. Conclusion: In phantoms, images from MIP with TEW scatter correction could detect all rods down to those with a diameter of 4 mm. In patients, MIP reconstruction with TEW scatter correction could improve the detectability of hot lesions. In addition, the time between injection and imaging could be shortened from that conventionally used for whole body scans.

Keywords: merged SPECT, MIP, TEW scatter correction, 99mTc-HMDP

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Authors: Nur Aziza Luxfiati

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Clustering is partitioning data sets into sub-sets or groups in such a way that elements certain properties have shared property settings with a high level of similarity within one group and a low level of similarity between groups. . The K-Means algorithm is one of thealgorithmsclustering as a grouping tool that is most widely used in scientific and industrial applications because the basic idea of the kalgorithm is-means very simple. In this research, applying the technique of clustering using the k-means algorithm as a method of solving the problem of national development imbalances between regions in Central Java Province based on macroeconomic indicators. The data sample used is secondary data obtained from the Central Java Provincial Statistics Agency regarding macroeconomic indicator data which is part of the publication of the 2019 National Socio-Economic Survey (Susenas) data. score and determine the number of clusters (k) using the elbow method. After the clustering process is carried out, the validation is tested using themethodsBetween-Class Variation (BCV) and Within-Class Variation (WCV). The results showed that detection outlier using z-score normalization showed no outliers. In addition, the results of the clustering test obtained a ratio value that was not high, namely 0.011%. There are two district/city clusters in Central Java Province which have economic similarities based on the variables used, namely the first cluster with a high economic level consisting of 13 districts/cities and theclustersecondwith a low economic level consisting of 22 districts/cities. And in the cluster second, namely, between low economies, the authors grouped districts/cities based on similarities to macroeconomic indicators such as 20 districts of Gross Regional Domestic Product, with a Poverty Depth Index of 19 districts, with 5 districts in Human Development, and as many as Open Unemployment Rate. 10 districts.

Keywords: clustering, K-Means algorithm, macroeconomic indicators, inequality, national development

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Authors: Abdon Choque-Rivero

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The Jacobi system with the Dirichlet boundary condition is considered on a half-line lattice when the coefficients are real valued. The inverse problem of recovery of the coefficients from various data sets containing the so-called transmission eigenvalues is analyzed. The Marchenko method is utilized to solve the corresponding inverse problem.

Keywords: inverse scattering, discrete system, transmission eigenvalues, Marchenko method

Procedia PDF Downloads 141

Authors: Valerii Dashuk

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The usage of the confidence intervals in economics and econometrics is widespread. To be able to investigate a random variable more thoroughly, joint tests are applied. One of such examples is joint mean-variance test. A new approach for testing such hypotheses and constructing confidence sets is introduced. Exploring both the value of the random variable and its deviation with the help of this technique allows checking simultaneously the shift and the probability of that shift (i.e., portfolio risks). Another application is based on the normal distribution, which is fully defined by mean and variance, therefore could be tested using the introduced approach. This method is based on the difference of probability density functions. The starting point is two sets of normal distribution parameters that should be compared (whether they may be considered as identical with given significance level). Then the absolute difference in probabilities at each 'point' of the domain of these distributions is calculated. This measure is transformed to a function of cumulative distribution functions and compared to the critical values. Critical values table was designed from the simulations. The approach was compared with the other techniques for the univariate case. It differs qualitatively and quantitatively in easiness of implementation, computation speed, accuracy of the critical region (theoretical vs. real significance level). Stable results when working with outliers and non-normal distributions, as well as scaling possibilities, are also strong sides of the method. The main advantage of this approach is the possibility to extend it to infinite-dimension case, which was not possible in the most of the previous works. At the moment expansion to 2-dimensional state is done and it allows to test jointly up to 5 parameters. Therefore the derived technique is equivalent to classic tests in standard situations but gives more efficient alternatives in nonstandard problems and on big amounts of data.

Keywords: confidence set, cumulative distribution function, hypotheses testing, normal distribution, probability density function

Procedia PDF Downloads 172